boot_ci {cutpointr} | R Documentation |

## Calculate bootstrap confidence intervals from a cutpointr object

### Description

Given a `cutpointr`

object that includes bootstrap results
this function calculates a bootstrap
confidence interval for a selected variable.
Missing values are removed before calculating the quantiles. In the case
of multiple optimal cutpoints all cutpoints / metric values are included
in the calculation.
Values of the selected variable are returned for the percentiles alpha / 2
and 1 - alpha / 2. The metrics in the bootstrap data frames of
`cutpointr`

are suffixed with `_b`

and `_oob`

to indicate
in-bag and out-of-bag, respectively. For example, to calculate quantiles
of the in-bag AUC `variable = AUC_b`

should be set.

### Usage

```
boot_ci(x, variable, in_bag = TRUE, alpha = 0.05)
```

### Arguments

`x` |
A cutpointr object with bootstrap results |

`variable` |
Variable to calculate CI for |

`in_bag` |
Whether the in-bag or out-of-bag results should be used for testing |

`alpha` |
Alpha level. Quantiles of the bootstrapped values are returned for (alpha / 2) and 1 - (alpha / 2). |

### Value

A data frame with the columns quantile and value

### See Also

Other main cutpointr functions:
`add_metric()`

,
`boot_test()`

,
`cutpointr()`

,
`multi_cutpointr()`

,
`predict.cutpointr()`

,
`roc()`

### Examples

```
## Not run:
opt_cut <- cutpointr(suicide, dsi, suicide, gender,
metric = youden, boot_runs = 1000)
boot_ci(opt_cut, optimal_cutpoint, in_bag = FALSE, alpha = 0.05)
boot_ci(opt_cut, acc, in_bag = FALSE, alpha = 0.05)
boot_ci(opt_cut, cohens_kappa, in_bag = FALSE, alpha = 0.05)
boot_ci(opt_cut, AUC, in_bag = TRUE, alpha = 0.05)
## End(Not run)
```

*cutpointr*version 1.1.2 Index]